equi-articulated-pose.github.io - Self-Supervised Category-Level Articulated Object Pose Estimation with Part-Level SE(3) Equivariance

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Description: Self-Supervised Category-Level Articulated Object Pose Estimation with Part-Level SE(3) Equivariance.

self-supervised learning (8) se(3) equivariant network (1) se(3) equivariant network

Example domain paragraphs

Category-level articulated object pose estimation aims to estimate a hierarchy of articulation-aware object poses of an unseen articulated object from a known category. To reduce the heavy annotations needed for supervised learning methods, we present a novel self-supervised strategy that solves this problem without any human labels. Our key idea is to factorize canonical shapes and articulated object poses from input articulated shapes through part-level equivariant shape analysis. Specifically, we first i

Visualization for experimental results on complete point clouds. Shapes drawn for every three shapes from the left side to the right side are the input point cloud , reconstructions , and the predicted canonical object shape . Some shapes are aligned to the same glboal frame just for a better view. Their global pose may vary when feeding into the network.

Visualization for experimental results on partial point clouds . Shapes drawn for every three shapes from the left side to the right side are the input point cloud, reconstructions, and the predicted canonical object shape.

Links to equi-articulated-pose.github.io (3)

• ericyi.github.io Li Yi
• autogpart.github.io AutoGPart: Intermediate Supervision Search for Generalizable 3D Part Segmentation
• meowuu7.github.io Xueyi Liu